Data blending is a method for combining data from two data sources. In contrast to a traditional left join, a blended result set includes all rows from the primary data source. For each row of the primary data source is joined with a single aggregated row of all rows of the secondary data source which match rows in the primary data source. The matching is based on specified linkages between entities of the data sources, and the aggregation of a measure of the second data source is performed based on the aggregation type associated with the measure.
The linked entities of one or both data sources may belong to a dimension hierarchy. Conventional blending is often unsuitable in such a scenario because the models of each data source may not exhibit the same level of granularity. In a further complication, the linked entities may reflect different hierarchies, including different types of hierarchies.